A RELATIONAL DATABASE MODEL OF THE INTERNATIONAL CONTAINER SHIPPING NETWORK

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Abstract

International container shipping is a complex system of interlocked stakeholders. Obtaining reliable data can be difficult and the data for specific routes and container
terminals change over time. Intermodal transportation has increased in importance
over the years. A relational database model was developed as a tool for stakeholders
interested in analyzing specific paths. The database uses data on transportation time,
variance of transportation time, transportation cost and green house gas emissions.
The user can specify their own set of locations, movements, containers, items and
transportation modes. The total logistics cost of a specific importing strategy can be
calculated for any path defined by the user. A Floyd-Warshall algorithm was implemented to allow for the shortest path between locations to be determined, based on the preferences of the user for either cost, time or CO2 emissions. In order to illustrate the capabilities of our model and because of our interest in the port of Halifax, we created a dataset from the distances between important locations
within the international container shipping system. Using this dataset, some example
calculations indicate that the port of Halifax and the port of Montreal could consider cooperating to form a hub-and-spoke relationship for European imports. In another example, the port of Halifax provides the fastest route for imports using the Suez Canal intending to reach Toronto but the cheapest total logistics cost route involves
using the port of NY/NJ. By using both the total logistics cost algorithms and the
shortest path algorithms, the examples illustrate how stakeholders in the container
transportation industry can analyze various routes, terminals and make informed
decisions.